Alzheimer's disease (AD), the most common form of dementia, affects over five million people in the United States. A vast majority of cases are the result of late-onset AD (LOAD), which has a wide variability in onset, progression and severity across the population. Although environment likely plays a large role, heritability estimates for LOAD are high, suggesting still-unidentified genes contribute to disease susceptibility and progression. Identification of these genes is important for understanding the pathophysiology of the disease and will provide information about pathways whose misregulation contributes to the development of AD. Identification of these loci has proven difficult in human studies due to complex genomes, environmental variation, and an overall lack of statistical power. Genetic reference panels such as the BXD panel of mice have been generated in order to model a portion of the genetic complexity of human populations while controlling for environmental factors. We will combine this BXD panel with an established AD mouse model in order to identify individual genetic variants that modify the onset and severity of disease. We hypothesize that the gene variants modulating memory deficits caused by the introduction of familial AD (FAD) mutations do so by regulating hippocampal neuronal excitability, which has been shown to correspond with the onset and severity of memory deficits in both normal aging and existing AD mouse models. We will measure memory function and beta-amyloid levels in our AD-BXD panel at two time points (2-4 mo and 10-12 mo) and perform subsequent genetic linkage mapping in order to identify genomic areas that correlate to disease progression. Candidate genes will be selected from these loci based on the results of a combination of knowledge-based bioinformatics, network modeling, functional analysis, and comparison to human data. Up to three candidate genes will be identified and their role in memory function and disease progression determined by manipulating gene expression using viral transduction and measuring effects on memory function and neuronal excitability. Experiments to rescue memory deficits and/or delay the onset of AD pathology will then be performed by altering expression of the top candidate gene (and a priori candidate Trpc3). Success will be determined by comparing the incidence and severity of memory deficits displayed across treatment groups at midlife. The identification of novel modifier loci and successful rescue of memory deficits will be a critical frst step toward the development of both mechanistic-based treatments and personalized gene therapies that would maintain cognitive function in elderly humans. Such treatments would reduce the vast burden of AD patient care currently facing our society - an estimated $200 billion annually, in addition to personal and emotional costs. The identification of predictive gen variants would also have the tremendous potential to provide biomarkers for earlier detection and more effective treatment in human patients.